Product Question Answering in E-Commerce: A Survey
February 16, 2023 ยท The Cartographer ยท ๐ Annual Meeting of the Association for Computational Linguistics
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"Title-pattern auto-detect: Product Question Answering in E-Commerce: A Survey"
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Authors
Yang Deng, Wenxuan Zhang, Qian Yu, Wai Lam
arXiv ID
2302.08092
Category
cs.CL: Computation & Language
Cross-listed
cs.IR
Citations
19
Venue
Annual Meeting of the Association for Computational Linguistics
Last Checked
23 hours ago
Abstract
Product question answering (PQA), aiming to automatically provide instant responses to customer's questions in E-Commerce platforms, has drawn increasing attention in recent years. Compared with typical QA problems, PQA exhibits unique challenges such as the subjectivity and reliability of user-generated contents in E-commerce platforms. Therefore, various problem settings and novel methods have been proposed to capture these special characteristics. In this paper, we aim to systematically review existing research efforts on PQA. Specifically, we categorize PQA studies into four problem settings in terms of the form of provided answers. We analyze the pros and cons, as well as present existing datasets and evaluation protocols for each setting. We further summarize the most significant challenges that characterize PQA from general QA applications and discuss their corresponding solutions. Finally, we conclude this paper by providing the prospect on several future directions.
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